## Load the API key
api_key <- Sys.getenv("ACS_API_KEY")
#load packages we may need
library(tidyverse)
library(lubridate)
library(gt)
library(paletteer)
library(ggridges)
library(plotly)
library(gtExtras)
library(sf)
library(tidycensus)
library(leaflet)
library(osmdata)
library(tigris)
library(ggplot2)
library(ggmap)
library(ggthemes)
library(viridis)Assignment 8
Task 3 from Assignment 6
#get health insurance data from ACS
mn_health <- get_acs(
geography = "tract",
variables = c("B27001_007" #uninsured
, "B01003_001" #population
),
state = "MN",
county = "Hennepin",
year = 2020,
geometry = TRUE,
cb = FALSE,
)
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|======================================================================| 100%mn_health_wide <- pivot_wider(
data = mn_health,
id_cols = c("GEOID", "geometry"),
names_from = "variable",
values_from = c("estimate", "moe")
)
#fraction percent uninsured
mn_health_wide$perc_uninsured <- mn_health_wide$estimate_B27001_007 / mn_health_wide$estimate_B01003_001
## create the map
health.gg <- ggplot() +
geom_sf(data = mn_health_wide,
aes(fill = perc_uninsured,
text = paste("Percentage uninsured: ",
scales::percent(perc_uninsured, accuracy = 0.1),
"<br>Total population: ", estimate_B01003_001))) +
labs(title = "Hennepin County 2020 ACS Health Insurance") +
theme_void() +
scale_fill_viridis_c("Percentage uninsured", labels = scales::percent_format(accuracy = 1)) +
guides(fill = guide_colorbar(title.position = "top", title.hjust = 0.5)) +
coord_sf(crs = st_crs("+proj=longlat +datum=WGS84")) # set the coordinate reference system to avoid warning
health.gg
ggplotly(health.gg, tooltip = "text") %>%
layout(title = "Hennepin County 2020 ACS Health Insurance",
xaxis = list(title = ""),
yaxis = list(title = ""))